Summary
Demonstrating high levels of independence in support of complex projects, they are responsible for collaborating with the clinical development team and members of the program team and across the organization more broadly, as well as identifying external partners to drive project execution by leveraging external innovation and resources.
Works with the function leads and teams in developing, leading and implementing key projects within the group and cross-functionally with partners efficiently and consistently to enable Development priorities and meet compliance standards.
May serve as on programs as a local manager of a small team or Individual contributor who is a thought leader with deep technical knowledge in data science, AI and machine learning, scientific knowledge and fluency, experience with drug development framework, stage gates and steps for advancing programs through registration..
Specifically, be the primary contact for data and AI, contributing to the data strategy, and support such projects in close collaboration with internal and external stakeholders e.g. program teams, clinical development teams, Precision Medicine, data42 and analytics.
About the Role
Major accountabilities:
- Lead data and AI projects for the Data Design & Clinical Innovation team
- Actively lead or participate in the identification of data gaps for scientific and clinical needs in clinical development in one or more therapeutic areas, and in the development and implementation of strategic solutions to these gaps for example:
- Evaluate the data quality from internal and external data sources for DDCI projects
- Collaborate with internal stakeholders to bring in external data to internal data platform
- Evaluate and implement AI solutions to improve the efficiency and effectiveness of clinical development programs
- Collaborate with data science groups to support the implementation of use cases and help identify work flows and techniques that may be reproducible
- Bridges scientific, technical, and drug development expertise to engage with clinical leads in CD, program teams, disease units, analytics, regulatory and commercial for data science and AI approaches
- Partner with Analytics and other Data Science organizations to plan and implement training and coaching in order to drive a culture of data and AI literacy and innovations to drive clinical development success.
- Track data science and AI projects within DDCI requiring inputs and support
- Scope and evaluate data science and AI technology solutions for drug development
- Ensure data transformation and analysis specifications to ensure completeness, correctness and adherence to department guidelines and SOPs as well as to applicable GxP requirements
Minimum Requirements:
- PhD (essential), Post Doc (desired) in data science, biostatistics, computational biology, bioengineering or related field
- 7 years of involvement in clinical research or drug development in an academic or industry environment.
- 5 years of contribution to and accomplishment in all aspects of data science, in a global/matrix environment in pharmaceutical industry
- Demonstrated ability to establish strong scientific partnership with key stakeholders
- Thorough knowledge of GCP, clinical trial design, statistical analysis methodology, and regulatory/clinical development process
- Scientific background in basic and clinical research with good understanding and knowledge on drug development.
- Strong skills in leading and managing cross-functional projects with significant (visible) business impact.
- Proficient in Python, SAS, R, and R-shiny; Building machine learning models utilizing high performance computing (HPC) environments
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Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.
